Before you grant an AI agent access to your internal documentation, consider the permission model. Most teams hand over 'read' access to everything in their digital workspace to get the chatbot working, assuming the tool is a walled garden. In reality, you are often training a model on your most sensitive strategy documents, client data, and internal grievances without any granular control over what the AI reveals to whom. If you are experimenting with LLMs in your office, start by compartmentalising your data into read-only zones rather than giving a broad-access pass to the entire server. A simple audit of your permissions now will save you from an embarrassing data leak later. How are you currently managing the data governance side of your AI experiments?
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